CN111106773B - Permanent magnet synchronous motor model prediction control method based on optimized duty ratio - Google Patents

Permanent magnet synchronous motor model prediction control method based on optimized duty ratio Download PDF

Info

Publication number
CN111106773B
CN111106773B CN202010007818.1A CN202010007818A CN111106773B CN 111106773 B CN111106773 B CN 111106773B CN 202010007818 A CN202010007818 A CN 202010007818A CN 111106773 B CN111106773 B CN 111106773B
Authority
CN
China
Prior art keywords
sampling period
voltage vector
duty ratio
opt3
vector
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202010007818.1A
Other languages
Chinese (zh)
Other versions
CN111106773A (en
Inventor
唐文博
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tianjin University
Original Assignee
Tianjin University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tianjin University filed Critical Tianjin University
Priority to CN202010007818.1A priority Critical patent/CN111106773B/en
Publication of CN111106773A publication Critical patent/CN111106773A/en
Application granted granted Critical
Publication of CN111106773B publication Critical patent/CN111106773B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/14Estimation or adaptation of machine parameters, e.g. flux, current or voltage
    • H02P21/141Flux estimation
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02PCONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/05Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation specially adapted for damping motor oscillations, e.g. for reducing hunting
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P80/00Climate change mitigation technologies for sector-wide applications
    • Y02P80/10Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Control Of Ac Motors In General (AREA)

Abstract

The invention discloses a permanent magnet synchronous motor model prediction control method based on optimized duty ratio, which comprises the following steps: considering time delay compensation, establishing a cost function for a reference value of the stator flux linkage vector and a predicted value error value, and obtaining a voltage vector which acts in the next sampling period and enables the cost function to be minimum and the acting time of the voltage vector in each sampling period through an exhaustion method; expressing the cost function as a function of the voltage vector action time t, and solving a partial derivative to enable the partial derivative to be zero to obtain the voltage vector action time topt which enables the cost function to be minimum; when the action time of the voltage vector calculated at the last sampling moment is longer than a sampling period, the vector can continue to act in the current sampling period, meanwhile, the optimal vector and the action time thereof can be obtained at the current sampling moment through an exhaustion method, and the duty ratio of the sampling period is determined according to the two optimal voltage vectors and the action time thereof. The invention can realize the purposes of inhibiting torque ripple and reducing current harmonic content under various working conditions.

Description

Permanent magnet synchronous motor model prediction control method based on optimized duty ratio
Technical Field
The invention relates to the field of motor systems and control, in particular to a permanent magnet synchronous motor model prediction control method based on optimized duty ratio.
Background
The permanent magnet synchronous motor has the advantages of high power density, high torque, simple structure and the like, and has wide application in the industrial fields of servo systems, electric automobiles, wind power generation and the like, so the research on the control algorithm of the permanent magnet synchronous motor is always a hot spot [1-3] . In recent years, predictive control has attracted extensive attention in the fields of motor control and the like because of its advantages of simple modeling, rolling optimization, effective solution to multivariable constrained systems, and the like [4-6]
The model predictive control is mainly divided into dead-beat model predictive control and finite set model predictive control [7] The finite set model predictive control is a very traditional permanent magnet synchronous motor predictive control method, 8 basic voltage vectors are taken as a basis and are brought into a value function through an exhaustion method, and the voltage vector which enables the value function to be minimum is obtained and is output as an optimal vector. However, since only one voltage vector can be used in one sampling period, the error between the given value and the actual value of the flux linkage vector is large [8] The method causes larger torque steady-state fluctuation and increases harmonic components in the current, and the problem of large steady-state fluctuation is more obvious along with the increase of the sampling period.
Using a multilevel converter [9,10] Or adding virtual vectors [11] Is a directly effective method to reduce steady state fluctuations in predictive control torque, but will do soThe problem of increased computational burden is caused, and the requirement on hardware is high. Some scholars propose a method for adding a zero vector in a sampling period, namely, an effective vector and a zero vector are acted in a sampling period, the duty ratio of the effective vector in the sampling period is calculated in advance, and in the predicted value of the stator flux linkage, the steady-state fluctuation of the torque is effectively reduced. However, only one effective vector exists in one sampling period, the stator flux linkage track only has one motion direction, and the torque steady state fluctuation is large; in addition, if the obtained optimal action time is greater than one sampling period and the action time of the effective vector is greater than one sampling period, the general processing mode makes the action time equal to one sampling period [12] It shows that the action time obtained at this time is invalid, which not only wastes computing resources, but also reduces the steady-state performance of the torque.
No matter which control strategy is adopted, the control effect of the system can not be improved under the same switching frequency. Therefore, a technology for improving the steady-state control effect of the finite set model predictive control and the traditional duty ratio model predictive control under the same switching frequency, suppressing the torque ripple and reducing the current harmonic content and maintaining the original rapid transient response is urgently needed to be provided.
Reference to the literature
[1]Siami M,Arab Khaburi D,Rivera M,et al.A Computationally Efficient Lookup Table Based FCS-MPC for PMSM Drives Fed by Matrix Converters[J].IEEE Transactions on Industrial Electronics,2017,64(10):7645-7654.
[2]Zhang X,Zhang L,Zhang Y,et al.Model predictive current control for PMSM drives with parameer ro-bustness improvement[J].IEEE Transactions on Power Electronics,2019,34(2):1645-1657.
[3] Improved predicted torque control of permanent magnet synchronous machines with parametric robustness [ J ] electrician technical report, 2018,33 (5): 965-972.
[4]Patricio C,Marian K,Ralph K,et al.Model predic-tive control in power electronics and drives[J].IEEE Transactions on Industrial Electronics,2008,55(12):4312-4324.
[5]Kouro S,Perez A,et al.Moder predictive con-trol:MPC’s role in the evolution of power electron-ics[J].IEEE Transactions on Industrial Electronics,2015,9(4):8-21.
[6]A.Achalhi,N.Belbounaguia,and M.Bezza,“A novel modified dtc scheme with speed fuzzy-pi controller,”in 20184th International Conference on Optimization and Applications(ICOA),Apr.2018,pp.1–5.
[7]Abdelsalam A,Byung K,YoungL.A comparison of finite controlset and continuous set modelpredictive controlschemes for speed controlofinduction mo-tors[J].IEEE Transactions on Industrial Informatics,2018,14(4):1334-1346.
[8]S.Kouro,P.Cortes,R.Vargas,U.Ammann,and J.Rodriguez,“Model predictive controla simple and powerful method to control power converters,”IEEE Trans.Ind.Electron.,vol.56,no.6,pp.1826–1838,Jun.2009.
[9]J.Rodriguez,Jih-Sheng Lai,and Fang Zheng Peng,“Multilevel inverters:a survey of topologies,controls,and applications,”IEEE Trans.Ind.Electron.,vol.49,no.4,pp.724–738,Aug.2002.
[10]S.Kouro,M.Malinowski,K.Gopakumar,J.Pou,L.G.Franquelo,B.Wu,J.Rodriguez,M.A.Prez,and J.I.Leon,“Recent advances and industrial applications of multilevel converters,”IEEE Trans.Ind.Electron.,vol.57,no.8,pp.2553–2580,Aug.2010.
[11]Zhou Z,Xia L,Yan Y,et al.Torque ripple minimization of predictive torque control for PMSM with extended control set[J].IEEE Transactions on Industrial Electronics,2017,64(9):6930-6939.
[12]Zhang C,Xie W.Low complexity model predictive control-Single vector-based approach[J].IEEE Trans-actions on Power Electronics,2014,29(10):5532-5540.
Disclosure of Invention
The invention provides a permanent magnet synchronous motor model prediction control method based on optimized duty ratio, which can realize the purposes of inhibiting torque pulsation and reducing current harmonic content under various working conditions, and is described in detail as follows:
a permanent magnet synchronous motor model predictive control method based on optimized duty cycle, the method comprising:
in consideration of time delay compensation, a cost function is established between a stator flux linkage vector reference value and a predicted value error value, and in each sampling period, a voltage vector which acts in the next sampling period and enables the cost function to be minimum and the acting time of the voltage vector can be obtained through an exhaustion method;
expressing the cost function as a function of the voltage vector action time t, and solving the partial derivative to make the partial derivative zero to obtain the voltage vector action time t which enables the cost function to be minimum opt
When the action time of the voltage vector calculated at the last sampling moment is longer than a sampling period, the vector can continue to act in the current sampling period, the optimal vector and the action time thereof can be obtained at the current sampling moment through an exhaustion method, and the duty ratio of the sampling period is determined according to the two optimal voltage vectors and the action time thereof.
The method further comprises the following steps: a new duty ratio updating scheme is provided to achieve the purpose of optimally controlling the permanent magnet synchronous motor.
The duty cycle updating scheme specifically comprises the following steps:
1)0≤t I1 ≤T s and t is opt3 +t I1 ≥T s
Phase a is taken as an example, and is assumed to be at (k-1) T s Calculating the optimal voltage vector u at any moment opt (k-1) the corresponding a-phase level is high at kT s Calculating the optimal voltage vector u at any moment opt (k) If the corresponding a-phase level is low, it is at (k + 1) T s Duty ratio of time action: da = t II2 /T s
Updating t II2 And t I1 The value of (c):
t II2 =t I1
t I1 =t opt3 +t II2 -T s
when t is opt3 +t I1 ≥2T s Time, meaning that the action time obtained at the current moment is greater than one sampling period, at (k + 1) T s The calculation of the voltage vector is not carried out at any moment, the voltage vector of the previous sampling period continues to act in the current sampling period, and the updating mode of the duty ratio is as follows: t is t I1 =t I1 -T s ;t II2 =0, until 0 ≦ t I1 Calculating the voltage vector again when Ts is less than or equal to Ts;
2)0≤t I1 ≤T s and t is opt3 +t I1 ≤T s
Similar to the first case, t II2 And t I1 The value is updated in the manner shown in the above formula, with t I1 Is set to 0;
3)0≤t I1 t is less than or equal to 0 opt3 +t I1 ≥T s
Take phase a as an example, when u opt (k) When the corresponding level is 1, d is set a =1, otherwise d a =0; at kT s Time of day update t II2 And t I1 Value of (a), t II2 ≤0、t I1 =t opt3 -T s A handle t II2 Is set to 0;
when t is opt3 ≥2T s It indicates that the action time calculated at the current moment is more than two sampling periods at (k + 1) T s The duty ratio of the sampling period is only related to the voltage vector calculated at the previous sampling moment, and the updating mode of the duty ratio is as follows: t is t I1 =t I1 -T s ;t II2 =0, until 0 ≦ t I1 ≤T s Calculating the voltage vector again;
4)0≤t I1 t is less than or equal to 0 opt3 +t I1 ≤T s
When u is opt (k) When the corresponding level is 1, d a =t opt3 /T s Otherwise, d a =0; at kT s The time is updated to t II2 And t I1 After a value of (d), t II2 ≤0、t I1 =t opt3 -T s Not more than 0, t II2 And t I1 The value of (d) is set to 0.
The technical scheme provided by the invention has the beneficial effects that:
1. the method considers the influence of the optimal voltage vector and the action time of the optimal voltage vector in the last sampling period on the duty ratio of the current sampling period, and simultaneously determines the duty ratio of the current sampling period together based on the voltage vector and the action time at the current sampling moment;
2. the invention provides a sampling period duty ratio method for solving the problems that the stator flux linkage track in the traditional duty ratio prediction control strategy has only one motion direction, the torque steady state fluctuation is large and the like, and the duty ratio of each sampling period is optimized;
3. according to the invention, a brand-new duty ratio updating method is provided at each sampling moment according to the two optimal voltage vectors and the action time thereof, so that the steady-state torque fluctuation is effectively reduced.
Drawings
FIG. 1 is a schematic diagram of a stator flux linkage track predicted and controlled by a conventional duty ratio model (the action time of a voltage vector is fixed to a sampling period T) s );
FIG. 2 is a schematic diagram of a stator flux linkage trajectory when a control strategy optimization duty cycle model is used for predictive control;
FIG. 3 shows that when t is 0. Ltoreq. T I1 ≤T s And t is opt3 +t I1 ≥T s Meanwhile, a schematic diagram of a sampling period duty ratio updating method is shown;
FIG. 4 shows that when t is 0. Ltoreq.t I1 ≤T s And t is opt3 +t I1 ≤T s Meanwhile, a schematic diagram of a sampling period duty ratio updating method is shown;
FIG. 5 shows that when t is 0. Ltoreq.t I1 ≤T s And t is opt3 +t I1 ≥T s Meanwhile, a schematic diagram of a sampling period duty ratio updating method is shown;
FIG. 6 shows that when t is 0. Ltoreq. T I1 ≤T s And t is opt3 +t I1 ≤T s And (3) a schematic diagram of a sampling period duty ratio updating method.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention are described in further detail below.
In order to meet the high performance requirements of important application occasions such as aviation and automobiles, the permanent magnet synchronous motor is required to improve the control effect of torque under the condition of not increasing switching loss. The invention mainly analyzes the principles of a traditional finite set model predictive control strategy and a traditional duty ratio model predictive control strategy, and provides a permanent magnet synchronous motor predictive flux linkage control method based on optimized duty ratio aiming at the problem that the torque fluctuation of the finite set predictive control strategy and the traditional duty ratio model predictive control strategy is large.
The basic idea is as follows: when the action time of the voltage vector calculated at the last sampling moment is longer than a sampling period, the vector can continue to act in the current sampling period, meanwhile, the optimal vector and the action time thereof can be obtained at the current sampling moment through an exhaustion method, and the duty ratio of the sampling period is determined according to the two effective vectors and the action time thereof.
Example 1
A permanent magnet synchronous motor model prediction control method based on optimized duty ratio comprises the following steps:
101: establishing a mathematical model of the permanent magnet synchronous motor, wherein the model is the basis of a subsequent permanent magnet synchronous motor prediction control algorithm;
102: considering time delay compensation, establishing a cost function for the reference value of the stator flux linkage vector and the error value of the predicted value, and obtaining a voltage vector which acts in the next sampling period and enables the cost function to be minimum and the acting time of the voltage vector in each sampling period by an exhaustion method;
103: expressing the cost function as a function of the voltage vector action time t, and solving the partial derivative to make the partial derivative zero to obtain the voltage vector action time t which enables the cost function to be minimum opt
104: when the action time of the voltage vector calculated at the last sampling moment is longer than a sampling period, the vector can continue to act in the current sampling period, meanwhile, the optimal vector and the action time thereof can be obtained at the current sampling moment through an exhaustion method, and the duty ratio of the sampling period is determined according to the two optimal voltage vectors and the action times thereof, so that the steady-state performance of the traditional duty ratio model prediction control can be effectively improved;
105: in order to facilitate the implementation of the algorithm, a new duty ratio updating scheme is provided to achieve the purpose of optimally controlling the permanent magnet synchronous motor.
Example 2
The scheme in example 1 is further described below with reference to specific examples and calculation formulas, which are described in detail below:
1. finite set model predictive control
A mathematical model of the permanent magnet synchronous motor is established under a two-phase static coordinate system, and the relation between stator flux linkage and voltage can be expressed as follows:
Figure BDA0002355971230000061
in the formula, /) s And psi r Respectively a stator flux linkage and a rotor flux linkage; r s And L s Respectively a stator resistor and a stator inductor; u. u s And i s Stator voltage and stator current, respectively.
Electromagnetic torque T e The expression is as follows:
Figure BDA0002355971230000062
in the formula, p represents the number of pole pairs of the motor.
Angle theta between stator flux linkage and rotor flux linkage es Represents:
Figure BDA0002355971230000063
Figure BDA0002355971230000064
in the formula, # s And psi r Representing the amplitude of the stator flux linkage and the amplitude of the rotor flux linkage, respectively.
In the prediction modelGiven value psi of stator flux linkage s,ref The expression of (a) is:
Figure BDA0002355971230000065
Figure BDA0002355971230000066
in the formula, theta e Is the actual position of the rotor flux linkage; t is a unit of s Representing the control period of the system; omega e Representing the rotational speed of the stator flux linkage.
Under the condition of neglecting the stator resistance, discretizing the formula (1) by adopting a first-order Euler formula to obtain a prediction model of the flux linkage:
ψ s (k+2)=ψ s (k)+u i (k+1)T s +u opt (k)T s (5)
in the formula u i (k + 1) represents the voltage vectors corresponding to the different switch states, including u 1 ···u 6 Six significant vectors, and u 0 And u 7 Two zero vectors; k represents a sampling instant; u. of opt (k) Represents the optimal voltage vector acting at time k; psi s (k) Representing the actual value of the stator flux linkage at the current moment.
That is, the above equations (1) to (5) constitute a mathematical model of the permanent magnet synchronous motor, which is also the basis of the subsequent permanent magnet synchronous motor predictive control algorithm.
The limited set model predictive control utilizes 8 voltage vectors to control the torque of the motor, firstly constructs a cost function shown in an equation (6), and then selects the voltage vector which enables the cost function to take the minimum value as output. Obviously, the online optimization algorithm directly combined with the controlled object can conveniently solve related problems such as overcurrent.
g=(ψ sα,ref (k+2))+(ψ sβ,ref (k+2))
(6)
In the formula, # sα,ref And psi sβ,ref Respectively representing the given values of the magnetic flux linkage on the alpha and beta axes.
Because only one voltage vector acts in one sampling period, the inverter can only change the switching state at the sampling point moment, and the problems of large steady-state fluctuation of the torque and the like are inevitably generated.
2. Conventional duty cycle model predictive control
Compared with the finite set model predictive control, the duty ratio predictive control increases the duty ratio calculation, two voltage vectors (effective vector + zero vector) are selected in one sampling period, and the effective vector action time is obtained by solving the partial derivative of the cost function, so that the duty ratio of the effective vector in one sampling period is obtained. Due to the characteristics of the digital signal processor, the duty ratio obtained at the current sampling moment needs to act at the next sampling moment, and the predicted value psi of the stator flux linkage is considered in consideration of delay compensation s,pre Comprises the following steps:
ψ s,pre =ψ s (k)+u opt (k)t opt (k)+u i (k+1)t i (k+1) (7)
in the formula, t opt (k) Represents the optimal voltage vector at kT s Time of day optimum action time, t i (k + 1) is the effective voltage vector at (k + 1) T s The duration of the cycle.
Similarly, the cost function is established as shown in equation (8), and it is obvious that the cost function is related to time t i And (k + 1) calculating a derivative and making the derivative zero to obtain the action time of the effective voltage vector, and substituting the cost function to obtain the optimal voltage vector by using an exhaustion method.
g=(ψ sα,ref (k+2))+(ψ sβ,ref (k+2)) (8)
By solving:
Figure BDA0002355971230000071
the following can be obtained:
Figure BDA0002355971230000072
from the above analysis, firstly, only one effective vector can be used in one sampling period, the stator flux linkage has only one rotation direction, the fluctuation of torque and flux linkage in a steady state is increased, and secondly, the action time t obtained by derivation opt (k + 1) is greater than one sampling period T s The action time obtained at this time is ineffective. Based on the method, the optimized duty ratio model prediction control is provided.
3. Optimized duty ratio model prediction flux linkage control strategy implementation process
The first step is as follows: as shown in fig. 3, a predicted value of the stator flux linkage at the current sampling time is established:
ψ s,pre =ψ s (k)+u opt (k)t II2 +u opt (k+1)t opt2 +u i (k+2)t opt3 (11)
wherein u is opt (k) To be at kT s The optimal voltage vector t obtained by time calculation II2 Is (k-1) T s The time of day is expressed as shown in fig. 3 for the voltage vector action time updated for the convenience of implementation of the algorithm.
The second step: according to the formulas (8), (9) and (10), the voltage vector which minimizes the cost function and the action time thereof are obtained by an exhaustion method and are used as the output of the next sampling moment, namely t opt3 And u opt (k+2)。
The third step: t obtained based on last sampling time opt2 And u opt (k + 1) and t obtained at the current sampling time opt3 And u opt And (k + 2) which jointly determine the duty cycle of the next sampling period.
4. Digital implementation of optimized duty cycle model predictive flux linkage control
T obtained based on previous sampling instant I1 And t obtained at the current time opt3 The updating method of the duty ratio is mainly divided into the following four cases:
1)0≤t I1 ≤T s and t is opt3 +t I1 ≥T s As shown in fig. 3.
The optimal voltage vector calculated at the current moment will be (k + 2) T s Continues to act during the sampling period, affecting (k + 2) T s Duty cycle of the sampling period; and the voltage vector obtained at the previous sampling moment is (k + 1) T s Continues to function during the sampling period, thus (k + 1) T s The duty cycle of the sampling period is changed accordingly. Meanwhile, the influence of the level on the duty ratio needs to be considered, taking the phase a in three-phase voltage as an example, the voltage is assumed to be at (k-1) T s Calculating the optimal voltage vector u at any moment opt (k-1) the corresponding a-phase level is high at kT s Calculating the optimal voltage vector u at any moment opt (k) The corresponding a-phase level is low, and is at (k + 1) T s Duty ratio of time action: da = t II2 /T s . To facilitate the calculation of the vector contribution time at the next sampling instant, t needs to be updated II2 And t I1 The value of (c):
t II2 =t I1
t I1 =t opt3 +t II2 -T s (12)
when t is opt3 +t I1 ≥2T s Time, meaning that the action time obtained at the current moment is greater than one sampling period, at (k + 1) T s The calculation of the voltage vector is not carried out at any moment, the voltage vector of the previous sampling period continues to act in the current sampling period, and the duty ratio is updated in the following mode: t is t I1 =t I1 -T s ;t II2 =0, until 0 ≦ t I1 And (5) Ts, calculating the voltage vector again.
2)0≤t I1 ≤T s And t is opt3 +t I1 ≤T s As shown in fig. 4.
The optimal vector calculated at the current sampling moment does not influence the duty ratio calculation of the next sampling period any more, but the voltage vector calculated at the previous sampling moment still influences the duty ratio calculation of the current sampling period. Similar to the first case, t II2 And t I1 The update mode of the value is shown in equation (12). From the formula (12), t is known I1 Less than or equal to 0 isIs convenient for predicting value psi of next sampling moment s,pre To reduce the complexity of the algorithm, t needs to be calculated I1 Is set to 0.
3)0≤t I1 T is less than or equal to 0 opt3 +t I1 ≥T s As shown in fig. 5.
The optimal voltage vector calculated at the last sampling moment does not influence the duty ratio of the next sampling period any more, but the optimal voltage vector calculated at present influences the duty ratio of the next sampling period. At this time, there are only two relations between the level and the duty ratio corresponding to the voltage vector, taking phase a as an example, when u is opt (k) When the corresponding level is 1, d is set a =1, otherwise d a =0. At kT s Time of day update t II2 And t I1 Value of (a), t II2 ≤0、t I1 =t opt3 -T s To calculate the predicted value, t is required to be calculated II2 The value of (d) is set to 0.
As mentioned above, when t opt3 ≥2T s It is shown that the calculated action time at the current moment is greater than two sampling periods, at (k + 1) T s The duty ratio of the sampling period is only related to the voltage vector calculated at the previous sampling moment, and the updating mode of the duty ratio is as follows: t is t I1 =t I1 -Ts;t II2 =0 until 0 ≦ t I1 ≤T s The voltage vector is calculated again.
4)0≤t I1 T is less than or equal to 0 opt3 +t I1 ≤T s As shown in fig. 6.
At this time, the duty ratio of the current sampling period is no longer influenced by the optimal voltage vector calculated at the previous sampling moment, the duty ratio of the next sampling period is no longer influenced by the optimal voltage vector calculated at the current sampling moment, the relationships between the levels corresponding to the voltage vectors and the duty ratios are only two, and similarly, taking phase a as an example, when phase u is used as the case opt (k) When the corresponding level is 1, d is set a =t opt3 /T s Otherwise, d a And =0. At kT s The time is updated to t II2 And t I1 After a value of (d), t II2 ≤0、t I1 =t opt3 -T s 0 or less, the same, for convenience of calculationMeasured value, t II2 And t I1 The value of (d) is set to 0.
In the embodiment of the present invention, except for the specific description of the model of each device, the model of other devices is not limited, as long as the device can perform the above functions.
Those skilled in the art will appreciate that the drawings are only schematic illustrations of preferred embodiments, and the above-mentioned serial numbers of the embodiments of the present invention are only for description and do not represent the merits of the embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the present invention, which is intended to cover any modifications, equivalents, improvements, etc. within the spirit and scope of the present invention.

Claims (1)

1. A permanent magnet synchronous motor model prediction control method based on optimized duty ratio is characterized by comprising the following steps:
in consideration of time delay compensation, a cost function is established between a stator flux linkage vector reference value and a predicted value error value, and in each sampling period, a voltage vector which acts in the next sampling period and enables the cost function to be minimum and the acting time of the voltage vector can be obtained through an exhaustion method;
expressing the cost function as a function of the voltage vector action time t, and solving the partial derivative to make the partial derivative zero to obtain the voltage vector action time t which enables the cost function to be minimum opt
When the action time of the voltage vector calculated at the last sampling moment is longer than a sampling period, the vector can continue to act in the current sampling period, the optimal vector and the action time thereof can be obtained at the current sampling moment through an exhaustion method, and the duty ratio of the sampling period is determined according to the two optimal voltage vectors and the action time thereof;
the duty cycle updating scheme specifically comprises the following steps:
1)0≤t I1 ≤T s and t is opt3 +t I1 ≥T s
Phase a is taken as an example, and is assumed to be at (k-1) T s Calculating the optimal voltage vector u at any moment opt (k-1) The corresponding a-phase level is high, at kT s Calculating the optimal voltage vector u at any moment opt (k) The corresponding a-phase level is low, T s Is a sampling period;
at (k + 1) T s Duty ratio of time action: da = t II2 /T s (ii) a Updating t II2 And t I1 The value of (c):
t II2 =t I1
t I1 =t opt3 +t II2 -T s
when t is opt3 +t I1 ≥2T s Time, meaning that the action time obtained at the current moment is greater than one sampling period, at (k + 1) T s The calculation of the voltage vector is not carried out at any moment, the voltage vector of the previous sampling period continues to act in the current sampling period, and the updating mode of the duty ratio is as follows: t is t I1 =t I1 -T s ;t II2 =0 until 0 ≦ t I1 ≤T s Calculating the voltage vector again;
2)0≤t I1 ≤T s and t is opt3 +t I1 ≤T s
Similar to the first case, t II2 And t I1 The value is updated in the manner shown in the above formula, with t I1 Is set to 0;
3)0≤t I1 t is less than or equal to 0 opt3 +t I1 ≥T s
Taking phase a as an example, when u opt (k) When the corresponding level is 1, d is set a =1, otherwise d a =0; at kT s Time of day update t II2 And t I1 Value of (a), t II2 ≤0、t I1 =t opt3 -T s Setting the value of tII2 to 0;
when t is opt3 ≥2T s It indicates that the action time calculated at the current moment is more than two sampling periods at (k + 1) T s The duty ratio of the sampling period is only related to the voltage vector calculated at the previous sampling moment, and the updating mode of the duty ratio is as follows: t is t I1 =t I1 -Ts;t II2 =0, until 0 ≦ t I1 ≤T s Calculating the voltage vector again;
4)0≤t I1 t is less than or equal to 0 opt3 +t I1 ≤T s
When u is opt (k) When the corresponding level is 1, d a =t opt3 /T s Otherwise, d a =0; at kT s The time is updated to t II2 And t I1 After a value of (d), t II2 ≤0、t I1 =t opt3 -T s Not more than 0, t II2 And t I1 The value of (d) is set to 0.
CN202010007818.1A 2020-01-05 2020-01-05 Permanent magnet synchronous motor model prediction control method based on optimized duty ratio Active CN111106773B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010007818.1A CN111106773B (en) 2020-01-05 2020-01-05 Permanent magnet synchronous motor model prediction control method based on optimized duty ratio

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010007818.1A CN111106773B (en) 2020-01-05 2020-01-05 Permanent magnet synchronous motor model prediction control method based on optimized duty ratio

Publications (2)

Publication Number Publication Date
CN111106773A CN111106773A (en) 2020-05-05
CN111106773B true CN111106773B (en) 2023-04-07

Family

ID=70426742

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010007818.1A Active CN111106773B (en) 2020-01-05 2020-01-05 Permanent magnet synchronous motor model prediction control method based on optimized duty ratio

Country Status (1)

Country Link
CN (1) CN111106773B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112072909B (en) * 2020-09-07 2022-03-25 电子科技大学 Drive signal modulation method for inhibiting electromagnetic interference of electric vehicle power module

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103762926A (en) * 2014-01-21 2014-04-30 华中科技大学 Model prediction-based torque control method for flux-switching permanent magnet synchronous machine
CN109379013A (en) * 2018-11-30 2019-02-22 北京理工大学 A kind of permanent magnet synchronous motor method for suppressing torque ripple
CN110336501A (en) * 2019-07-10 2019-10-15 河北工业大学 A kind of IPM synchronous motor model predictive control method

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109600085B (en) * 2018-12-05 2020-08-14 天津工业大学 Permanent magnet synchronous motor direct prediction duty ratio control method based on variable control set
CN109861609B (en) * 2019-01-17 2021-07-30 天津工业大学 Five-bridge arm two-permanent magnet motor system optimization model prediction control device and method
CN110445438B (en) * 2019-06-28 2020-11-10 天津大学 Permanent magnet synchronous motor prediction flux linkage control method based on extended control set
CN110492821B (en) * 2019-08-27 2021-02-09 天津大学 Permanent magnet motor direct flux linkage control method based on unfixed vector action time

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103762926A (en) * 2014-01-21 2014-04-30 华中科技大学 Model prediction-based torque control method for flux-switching permanent magnet synchronous machine
CN109379013A (en) * 2018-11-30 2019-02-22 北京理工大学 A kind of permanent magnet synchronous motor method for suppressing torque ripple
CN110336501A (en) * 2019-07-10 2019-10-15 河北工业大学 A kind of IPM synchronous motor model predictive control method

Also Published As

Publication number Publication date
CN111106773A (en) 2020-05-05

Similar Documents

Publication Publication Date Title
CN110995076A (en) Permanent magnet synchronous motor model prediction current control method
CN110445441B (en) Permanent magnet synchronous motor predicted torque control method
CN110011588B (en) Semi-control open winding permanent magnet synchronous generator model prediction flux linkage control method
Zerdali et al. Speed-sensorless predictive torque controlled induction motor drive withfeed-forward control of load torque for electric vehicle applications
Zhang et al. Two-stage series model predictive torque control for PMSM drives
CN114172412A (en) Non-parameter model prediction current control method for double three-phase permanent magnet motor
CN113708688A (en) Permanent magnet motor vector reduction model prediction control method
CN112217437A (en) Permanent magnet synchronous motor three-vector model prediction current control circuit and method
CN114679095A (en) Permanent magnet motor finite set model prediction current control method based on disturbance compensation
Hu et al. A new predictive torque control based torque sharing function for switched reluctance motors
CN112910359A (en) Improved permanent magnet synchronous linear motor model prediction current control method
CN113179065A (en) Permanent magnet synchronous motor model prediction pulse sequence control method
Wang et al. Improved deadbeat control for PMSM with terminal sliding mode observer
CN111106773B (en) Permanent magnet synchronous motor model prediction control method based on optimized duty ratio
CN111130419A (en) Permanent magnet motor prediction flux linkage control method based on extended step length and variable action time
CN111900907A (en) Permanent magnet motor model prediction flux linkage control method based on switching point optimization
CN111049458A (en) Permanent magnet synchronous motor current control method based on variable vector action duration
CN115833690A (en) Six-phase permanent magnet synchronous motor parameter-free model prediction current control system and method
Tarvirdilu-Asl et al. Finite control set model predictive control for switched reluctance motor drives with reduced torque tracking error
CN115276501A (en) Dead-beat prediction current control method for permanent magnet synchronous motor
CN113691179A (en) Permanent magnet synchronous motor sliding mode control method based on variable power exponent approach law of fixed time
Xiang et al. Speed regulation of PMSM system based on nonsingular terminal sliding mode control
CN113285634A (en) Permanent magnet synchronous motor high-speed weak magnetic control method and system based on multi-step zero delay model prediction
Liu et al. Model Predictive Torque Control of NPC Three-Level Inverter for Induction Motor Based on Generalized Two-Vectors Considering Neutral-Point Potential Balance
CN114189184B (en) Six-phase motor model predictive control method for reducing harmonic content

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant